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https://github.com/PaddlePaddle/FastDeploy.git
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Move cpp code to directory csrcs
(#42)
* move cpp code to csrcs * move cpp code to csrcs
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@@ -1,144 +0,0 @@
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// Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved.
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//
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// Licensed under the Apache License, Version 2.0 (the "License");
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// you may not use this file except in compliance with the License.
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// You may obtain a copy of the License at
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//
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// http://www.apache.org/licenses/LICENSE-2.0
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//
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// Unless required by applicable law or agreed to in writing, software
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// distributed under the License is distributed on an "AS IS" BASIS,
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// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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// See the License for the specific language governing permissions and
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// limitations under the License.
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#include "fastdeploy/fastdeploy_model.h"
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#include "fastdeploy/utils/utils.h"
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namespace fastdeploy {
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bool FastDeployModel::InitRuntime() {
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FDASSERT(
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CheckModelFormat(runtime_option.model_file, runtime_option.model_format),
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"ModelFormatCheck Failed.");
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if (runtime_initialized_) {
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FDERROR << "The model is already initialized, cannot be initliazed again."
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<< std::endl;
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return false;
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}
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if (runtime_option.backend != Backend::UNKNOWN) {
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if (runtime_option.backend == Backend::ORT) {
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if (!IsBackendAvailable(Backend::ORT)) {
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FDERROR
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<< "Backend::ORT is not complied with current FastDeploy library."
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<< std::endl;
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return false;
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}
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} else if (runtime_option.backend == Backend::TRT) {
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if (!IsBackendAvailable(Backend::TRT)) {
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FDERROR
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<< "Backend::TRT is not complied with current FastDeploy library."
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<< std::endl;
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return false;
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}
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} else if (runtime_option.backend == Backend::PDINFER) {
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if (!IsBackendAvailable(Backend::PDINFER)) {
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FDERROR << "Backend::PDINFER is not compiled with current FastDeploy "
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"library."
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<< std::endl;
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return false;
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}
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} else {
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FDERROR
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<< "Only support Backend::ORT / Backend::TRT / Backend::PDINFER now."
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<< std::endl;
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return false;
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}
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runtime_ = new Runtime();
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if (!runtime_->Init(runtime_option)) {
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return false;
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}
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runtime_initialized_ = true;
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return true;
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}
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if (runtime_option.device == Device::CPU) {
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return CreateCpuBackend();
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} else if (runtime_option.device == Device::GPU) {
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#ifdef WITH_GPU
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return CreateGpuBackend();
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#else
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FDERROR << "The compiled FastDeploy library doesn't support GPU now."
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<< std::endl;
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return false;
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#endif
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}
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FDERROR << "Only support CPU/GPU now." << std::endl;
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return false;
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}
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bool FastDeployModel::CreateCpuBackend() {
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if (valid_cpu_backends.size() == 0) {
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FDERROR << "There's no valid cpu backends for model: " << ModelName()
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<< std::endl;
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return false;
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}
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for (size_t i = 0; i < valid_cpu_backends.size(); ++i) {
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if (!IsBackendAvailable(valid_cpu_backends[i])) {
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continue;
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}
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runtime_option.backend = valid_cpu_backends[i];
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runtime_ = new Runtime();
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if (!runtime_->Init(runtime_option)) {
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return false;
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}
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runtime_initialized_ = true;
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return true;
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}
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FDERROR << "Found no valid backend for model: " << ModelName() << std::endl;
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return false;
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}
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bool FastDeployModel::CreateGpuBackend() {
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if (valid_gpu_backends.size() == 0) {
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FDERROR << "There's no valid gpu backends for model: " << ModelName()
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<< std::endl;
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return false;
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}
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for (size_t i = 0; i < valid_gpu_backends.size(); ++i) {
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if (!IsBackendAvailable(valid_gpu_backends[i])) {
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continue;
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}
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runtime_option.backend = valid_gpu_backends[i];
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runtime_ = new Runtime();
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if (!runtime_->Init(runtime_option)) {
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return false;
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}
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runtime_initialized_ = true;
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return true;
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}
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FDERROR << "Cannot find an available gpu backend to load this model."
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<< std::endl;
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return false;
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}
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bool FastDeployModel::Infer(std::vector<FDTensor>& input_tensors,
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std::vector<FDTensor>* output_tensors) {
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return runtime_->Infer(input_tensors, output_tensors);
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}
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void FastDeployModel::EnableDebug() {
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#ifdef FASTDEPLOY_DEBUG
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debug_ = true;
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#else
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FDWARNING << "The compile FastDeploy is not with -DENABLE_DEBUG=ON, so "
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"cannot enable debug mode."
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<< std::endl;
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debug_ = false;
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#endif
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}
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bool FastDeployModel::DebugEnabled() { return debug_; }
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} // namespace fastdeploy
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